GEO vs AEO: Generative vs Answer Engine Optimization
GEO (Generative Engine Optimization) targets AI systems that synthesize answers; AEO (Answer Engine Optimization) targets featured snippets and voice assistants. GEO is the broader, more recent discipline focused on LLM-based search (Google SGE, Perplexity, ChatGPT). AEO predates GEO and focuses on extracting direct answers for traditional search features.
Key Differences
- ✓ GEO: Optimizing for AI-generated answers (Google SGE, Perplexity, ChatGPT)
- ✓ AEO: Optimizing for featured snippets, voice search, knowledge panels
- ✓ Relationship: AEO is a subset of GEO; GEO is the broader discipline
- ✓ Strategy: Both emphasize direct answers and structured content
What is AEO (Answer Engine Optimization)? #
AEO emerged around 2017-2018 as a response to the rise of “answer engines”—search features that provide direct answers without requiring a click:
- Featured Snippets: The “position zero” box above organic results
- Voice Assistants: Siri, Alexa, Google Assistant
- Knowledge Panels: Entity information boxes
- People Also Ask: Expandable question boxes
AEO techniques include:
- Question-and-answer formatting
- Concise, extractable answers
- Schema markup for structured data
- FAQ page optimization
What is GEO (Generative Engine Optimization)? #
GEO is a broader discipline that emerged with the rise of LLM-powered search engines in 2023-2024. It addresses optimization for systems that:
- Synthesize answers from multiple sources (not just extract snippets)
- Cite sources as part of the generated response
- Understand context through semantic analysis, not just keyword matching
GEO platforms include:
- Google SGE: AI-generated overviews in Google Search
- Perplexity: AI-native search engine
- ChatGPT Browse: Web search within ChatGPT
- Microsoft Copilot: AI search in Edge and Windows
GEO vs AEO: Detailed Comparison #
| Aspect | AEO | GEO |
|---|---|---|
| Era | 2017-present | 2023-present |
| Target Systems | Featured snippets, voice assistants | LLM-powered search engines |
| Answer Type | Extracted from single source | Synthesized from multiple sources |
| Citation Model | Single source attribution | Multiple source citations |
| Content Format | Q&A pairs, lists, tables | Comprehensive, multi-dimensional |
| Key Signal | Direct answer availability | Information gain + trust + structure |
How GEO and AEO Relate #
Think of AEO as a subset or precursor of GEO:
AEO Techniques That Apply to GEO
- Direct answers in first paragraph
- FAQ structured data
- Question-based headings
- Concise, extractable statements
GEO Adds Beyond AEO
- Multiple source citation optimization
- Information gain (uniqueness)
- Comprehensive trust signals
- Semantic depth and context
When to Focus on Each #
Focus on AEO When... #
- Targeting featured snippets for specific queries
- Optimizing for voice search responses
- Trying to capture “position zero”
- Building FAQ pages
Focus on GEO When... #
- Targeting AI-generated search results (SGE, Perplexity)
- Building comprehensive guides and resources
- Establishing thought leadership with original research
- Competing for citations in synthesized answers
Do Both When... #
In most cases, you should optimize for both. GEO techniques generally support AEO goals, and vice versa. The GEO CORE framework addresses both traditional answer engines and generative engines.
The Evolution from AEO to GEO #
The progression looks like this:
- 1SEO Era (1990s-2010s): Optimize for ranking in link lists
- 2AEO Era (2017-2022): Optimize for featured snippets and voice
- 3GEO Era (2023-present): Optimize for AI-synthesized answers
Each era doesn't replace the previous—it adds a new layer. You still need SEO fundamentals, AEO best practices, and GEO optimization.
Related Resources #
Learn More
Product Manager at Seenos.ai. Pioneer in AEO research since 2024, exploring the convergence of SEO and GEO (Generative Engine Optimization). Led multiple AI-powered content optimization projects that achieved 300%+ citation increases in ChatGPT and Perplexity.